# Make Automations > Visual, no-code workflows in Make.com that move data between your apps without writing any code. Page: https://showcase.growlyze.cloud/tag/make 12 case studies in full below. # From a Signed DocuSign Contract to a Master Sheet Row and an Itinerary Slide > Turning a signed DocuSign travel contract into a master sheet row, a filed contract and an itinerary slide, automatically. Section: Make Automations Page: https://showcase.growlyze.cloud/case/make-docusign-contract-to-master-sheet-and-itinerary-slide ## Overview An internal operations automation for a group travel company that manages college formal events. When a group signs a travel contract in DocuSign, the operations team has several follow-up jobs: record the trip in the master ops spreadsheet, file the signed contract in the group’s Drive folder, and produce a Friday/Saturday/Sunday itinerary slide for the group. This scenario does those three jobs automatically as soon as a DocuSign envelope is completed. Built with Make, DocuSign, Google Apps Script, Anthropic Claude (claude-sonnet-4-6), Google Sheets, Google Slides and Google Drive. ## The Problem Each signed contract holds the details the team needs in several places: hotel names and room counts, check-in ages, buses, venues, event times, food and bar packages, and payment and task due dates. Moving these by hand into the master sheet, then building a customer-facing itinerary from them, is repetitive and easy to get wrong. ## The Solution A Make scenario that: - Triggers when a DocuSign envelope is completed. - Downloads the signed document. - Sends it to a Google Apps Script web app, which returns the contract’s fields as structured data. - Asks Claude to write the three-day itinerary text from those fields. - Routes the result down three paths: a new-contract path, an addendum path, and an archive path. Image: Part of the Make scenario: the DocuSign trigger and download, the HTTP call to the Apps Script web app, Claude, and a router that splits into Google Sheets, Slides and Drive paths. (https://showcase.growlyze.cloud/case-content/make-portfolio/image11.png) Image: An example three-day itinerary slide (group, dates, hotel and company details blurred for privacy). (https://showcase.growlyze.cloud/case-content/make-portfolio/image12.png) --- # A Slack Bot That Answers Trip Questions from an Ops Master Sheet > A Make scenario that lets a team member ask a plain-English trip question in Slack and get an answer drawn only from the ops master sheet. Section: Make Automations Page: https://showcase.growlyze.cloud/case/make-slack-bot-trip-questions-from-ops-master-sheet ## Overview An internal operations tool for a group travel team. The operations team keeps all trip data in one Google Sheet (a “MASTER” tab in the workbook “Master Ops Fall 26/Spring27”). Each row is one group trip, with columns for dates, destination, ops coordinator, sales rep, contracts, hotel and rooming, transport, events, task due dates, and payment status. This scenario lets a team member ask a plain-English question in Slack and get a structured answer drawn only from that sheet, without opening it and searching for the right row and column. Built with Make, Anthropic Claude (claude-sonnet-4-6), Google Sheets and Slack. ## The Problem The sheet is wide. The blueprint’s column list runs from column A to column BH, with more than 55 labelled fields per trip. Finding a single fact, such as a group’s hotel or room counts, means locating the right row, then scrolling to the right column. ## The Solution A six-module Make scenario, triggered by a webhook, that: - Receives the Slack question and channel. - Uses Claude to turn the question into structured search terms. - Searches the master sheet for matching trips. - Flattens the matching rows into text. - Uses Claude again to answer from that text only. - Posts the answer back to the same Slack channel. Image: The Make scenario: a custom webhook, Claude turning the question into search terms, a Google Sheets search, a text aggregator, Claude answering from the results, and a Slack message. (https://showcase.growlyze.cloud/case-content/make-portfolio/image13.png) Image: An example answer in Slack: the question, the search terms Claude worked out, and the matching groups with their dates and destination (group names blurred for privacy). (https://showcase.growlyze.cloud/case-content/make-portfolio/image14.png) --- # Newsletter Generator: From a Google Sheets Row to a Draft Campaign > A Make scenario that turns one row of a Google Sheets newsletter planner into a finished draft campaign in Campaign Monitor, in one of three layouts chosen by the editor. Section: Make Automations Page: https://showcase.growlyze.cloud/case/make-newsletter-generator-sheet-to-campaign-monitor ## Purpose A publishing business sends a regular email newsletter with news articles, sponsored posts, a destination report and a podcast episode. Building each issue by hand in the email tool means copying titles, images, excerpts and links into a template, block by block. This Make scenario lets the editors plan the whole issue in a Google Sheet and creates the campaign automatically. ## The Solution - An editor fills in one row of the newsletter sheet. It holds the titles, images, excerpts, links and category labels for three news posts and three sponsored posts, plus the destination report and the podcast episode. - The editor picks a template number (1, 2 or 3) and sets the Create Newsletter cell to “Create”. - On its schedule, the scenario searches the sheet for a row marked Create and takes one row at a time. - A router checks that a row was found and sends it down one of three routes, depending on the template number. - Each route has a code step that builds the full newsletter from the row. The first route builds the three-row layout. The other two build the mixed layout, with two posts side by side and one centred below, each with its own template. - An HTTP step sends the result to the Campaign Monitor API, which creates a draft campaign from the chosen template. - A final Google Sheets step updates the row with “Done”. Image: The Make scenario: Google Sheets searches for a row marked Create, a router picks one of three templates, a code step builds the newsletter content, an HTTP call creates the campaign from the template, and Google Sheets updates the row. A Skip step on each route handles errors. (https://showcase.growlyze.cloud/case-content/make-newsletter-generator/image1.png) ## What the Code Builds - The newsletter is built section by section: a top banner, the news posts, a banner, the sponsored posts, the destination report, the podcast episode and a second banner. - Each news and sponsored post gets its image, a category label, its title and excerpt, and a button (Read More or Learn More) linked to the post. - The destination report has an image, a badge, the destination name, a description and a Read Full Report button. The podcast block has an image, a date line, the title, a description and a Listen Now button. - Gaps are filled in for the editors. A missing image on a news or sponsored post is replaced by a default image, a missing link points to the main website, and every issue gets a unique campaign name with a timestamp. - The subject line and the header date default to the current month and year, and the sender details and subscriber list are set in the same step. ## Good to Know - The editors work only in the sheet. All copy, images and links live there, so nobody has to open Make or edit a template to produce an issue. - The campaign is created as a draft in Campaign Monitor, so the team can check it there before it is sent. - If Campaign Monitor returns an error, the scenario skips that run instead of stopping with an error. --- # Automation of Shopify Orders to Google Sheets for Dropshipping E-commerce Store > The primary goal of this automation is to streamline the process of managing Shopify orders by automatically distributing them to the appropriate fulfillment sheets. Section: Make Automations Page: https://showcase.growlyze.cloud/case/make-automation-of-shopify-orders-to-google The primary goal of this automation is to streamline the process of managing Shopify orders by automatically distributing them to the appropriate fulfillment sheets. This is particularly useful for a dropshipping e-commerce store that sources products from multiple suppliers, such as AliExpress. - Order Creation: Whenever a new order is created in Shopify, the automation system adds it to a data store built within Make, making sure all orders are logged and tracked efficiently. - Product Identification: The automation includes a scenario that checks the product IDs in a Google Sheets database. By matching these product IDs, the system determines which specific fulfillment sheet each order should be directed to, based on the supplier. - Master Sheet Integration: A master sheet is maintained where all order data is consolidated. This master sheet serves as the central point for tracking and managing all orders. Whenever any changes are made to the master sheet, the automation ensures that these updates are reflected in the respective Google Sheets, maintaining consistency and accuracy across all fulfillment sheets. - Supplier Coordination: By automating the distribution of orders to the correct fulfillment sheets, the system ensures that each supplier receives the correct order information, facilitating efficient and accurate order fulfillment. Image (https://showcase.growlyze.cloud/case-content/make-portfolio/image1.png) Image (https://showcase.growlyze.cloud/case-content/make-portfolio/image2.png) Image (https://showcase.growlyze.cloud/case-content/make-portfolio/image3.png) --- # Daily Slack Updates Make Scenario > The automation is designed to send daily updates to Slack. The data in Google Sheets is updated daily, and the KPI data is sent to Slack every day using a Make scenario. Section: Make Automations Page: https://showcase.growlyze.cloud/case/make-daily-slack-updates-make-scenario The automation is designed to send daily updates to Slack. The data in Google Sheets is updated daily, and the KPI data is sent to Slack every day using a Make scenario. Image (https://showcase.growlyze.cloud/case-content/make-portfolio/image4.png) --- # Automation of ClickUp and Google Sheets > This Make scenario is implemented whenever a task gets completed in ClickUp. Section: Make Automations Page: https://showcase.growlyze.cloud/case/make-automation-of-clickup-and-google-sheets - This Make scenario is implemented whenever a task gets completed in ClickUp. - The task details are then sent to Google Sheets. - Based on custom fields, the data is being sent to respective google sheet file Image (https://showcase.growlyze.cloud/case-content/make-portfolio/image5.png) --- # Integration of Shopify and ClickUp for Managing Refunded Orders > This scenario is built so that whenever there is a refunded order in Shopify, the order details are added to ClickUp as tasks. Section: Make Automations Page: https://showcase.growlyze.cloud/case/make-integration-of-shopify-and-clickup-for - This scenario is built so that whenever there is a refunded order in Shopify, the order details are added to ClickUp as tasks. - This integration is implemented to streamline the management of refunded orders. Image (https://showcase.growlyze.cloud/case-content/make-portfolio/image6.png) --- # Fulfilled Order Integration with ClickUp > This Make scenario is implemented so that whenever an order is fulfilled in Shopify, the order details are added to ClickUp. Section: Make Automations Page: https://showcase.growlyze.cloud/case/make-fulfilled-order-integration-with-clickup This Make scenario is implemented so that whenever an order is fulfilled in Shopify, the order details are added to ClickUp. Image (https://showcase.growlyze.cloud/case-content/make-portfolio/image7.png) --- # Automating IG RSS Feed to Pinterest Pin Creation > This automation is implemented to create a Pinterest pin whenever RSS data is received. Section: Make Automations Page: https://showcase.growlyze.cloud/case/make-automating-ig-rss-feed-to-pinterest - This automation is implemented to create a Pinterest pin whenever RSS data is received. - In this Make scenario, multiple text parsers are used to ensure the data is in the relevant form when creating the pin. - The automation ensures that all necessary information from the RSS feed is accurately extracted. - Data parsing helps in formatting the content appropriately for Pinterest. - This setup streamlines the process of keeping Pinterest updated with content from the RSS feed. - The automation reduces manual effort and ensures timely pin creation based on new RSS data. Image (https://showcase.growlyze.cloud/case-content/make-portfolio/image8.png) --- # Integration of RB2B with Go High Level and Beehiv > RB2B is a platform that collects website visitor profiles. Section: Make Automations Page: https://showcase.growlyze.cloud/case/make-integration-of-rb2b-with-go-high - RB2B is a platform that collects website visitor profiles. - When a profile is created in RB2B, that profile is added to Go High Level as a contact. - A deal is also created in Go High Level for the new contact. - Additionally, the email is added to Beehiv as a subscriber. Image (https://showcase.growlyze.cloud/case-content/make-portfolio/image9.png) --- # Integration of Go High Level with Beehiv > This scenario is implemented so that whenever the status of an opportunity is changed in Go High Level, the associated email is added to Beehiv as a subscriber. Section: Make Automations Page: https://showcase.growlyze.cloud/case/make-integration-of-go-high-level-with This scenario is implemented so that whenever the status of an opportunity is changed in Go High Level, the associated email is added to Beehiv as a subscriber. Image (https://showcase.growlyze.cloud/case-content/make-portfolio/image10.png) --- # AI-Powered Shopify Abandoned Cart Recovery System > An always-on automation that detects abandoned Shopify carts and sends personalized, AI-written recovery emails. Section: n8n Automations, Make Automations, AI Agents Page: https://showcase.growlyze.cloud/case/ecom-agent-ai-powered-shopify-abandoned-cart-recovery ### 1. The Problem: Abandoned Carts Were Leaving Revenue on the Table Before automation, abandoned carts were handled manually or not followed up at all: - Teams had to manually check Shopify for abandoned checkouts - Writing reminder emails took time and effort - Most carts were never followed up consistently - Emails were generic, not personalized - Delays caused customers to lose purchase intent **On average** - Each abandoned cart follow-up took 5–7 minutes - Most stores only followed up once per day or skipped entirely - Many potential sales were lost simply due to no timely reminder For stores with 40–60 abandoned carts per day, this resulted in: - 3–5 hours of manual work daily, or - No follow-up at all, leading to permanent revenue loss ### 2. Results After Automation After implementing the abandoned cart recovery automation: - Follow-up emails are sent automatically within the right time window - 100% of abandoned carts receive a recovery attempt - Email personalization happens instantly using AI - Manual work is reduced by 90–95% - Recovery emails are sent within minutes, not hours **Time & Revenue Impact** **Before** - ~6 minutes per cart - 50 carts/day = ~5 hours/day **After** - Fully automated - Human effort = near zero **Monthly time savings** ~100–120 hours saved per month **Revenue uplift (conservative example)** - If only 5–8% of abandoned carts convert - And average cart value is $50 - That’s $100–$200+ recovered per day - $3,000–$6,000+ per month in recovered revenue ### 3. The Solution: AI-Powered Abandoned Cart Recovery This system works like an always-on sales assistant: - Detects abandoned carts automatically - Waits before sending reminders to avoid spamming - Confirms the cart is still abandoned - Generates a personalized recovery email using AI - Sends the email instantly without manual input The entire process runs silently in the background. ### 4. How the Automation Works - Shopify provides abandoned checkout data - n8n controls timing and logic - AI writes friendly, personalized recovery emails - Gmail delivers messages directly to customers No dashboards to monitor. No buttons to click. ### 5. Business Value - Captures revenue that would otherwise be lost - Removes repetitive manual follow-up work - Improves customer experience with timely reminders - Ensures every cart gets equal attention - Scales automatically as store traffic grows ### 6. How You Can Duplicate This System Open the JSON file preview **Open the attached file** - Shopify Abandoned Checkout Recovery with Order Verification (1).json - Select all text (Ctrl/Cmd + A) and copy (Ctrl/Cmd + C) **Open Make.com** **Log in to Make.com** **Go to Scenarios** Click Create a new scenario **Choose Import Blueprint** - Paste the copied JSON and click Save - Save & name the scenario **Click Save** **Rename it to** **Shopify Abandoned Checkout Recovery with Order Verification** - Update connections (important) - Shopify - Reconnect your Shopify account - Ensure checkout status is set to abandoned - Delay module - Review delay timing (used to confirm the cart is still abandoned) - Filter / verification - Confirms checkout is not duplicated or already completed - OpenAI - Add your OpenAI API key - Verify the email body is generated correctly (no subject, no emojis) **Email (Gmail / SMTP)** - Reconnect email account - Map customer email dynamically - Subject: You left something behind - Test the scenario - Click Run once **Confirm flow** - Abandoned checkout detected - Cart rechecked - AI email generated - Recovery email sent - Enable the scenario - Turn the scenario ON - Set a schedule (e.g. every 15–60 minutes) The system now automatically sends AI-written recovery emails for verified abandoned checkouts. ### 7. Final Outcome **With this automation in place** - Abandoned cart recovery becomes reliable and consistent - Sales teams no longer chase carts manually - Customers receive timely, personalized reminders - Revenue increases without increasing workload This workflow transforms abandoned carts from a missed opportunity into an automated revenue recovery system.